1. Field of the Invention
The present invention relates to angle of arrival estimation for signals, and particularly to a system and method utilizing cross correlation for estimating the angle of arrival of a received signal by a switched beam antenna array.
2. Description of the Related Art
An adaptive array system (AAS) can steer a beam in any desired direction by setting the weights across the antenna array elements. AAS requires M receivers to estimate the angle of arrival (AoA), where M is the number of antenna elements in the array. The AoA estimation techniques that use AAS can operate at lower signal-to-noise ratios (SNRs) than the conventional switched beam system (SBS) technique, but has greater hardware and computational complexities.
The switched beam system (SBS) uses a fixed number of beams to scan the azimuth plane. The AoA is the angle of the beam with the highest received power or signal strength (RSS). The SBS is easy to implement since it requires a single receiver and no baseband signal processing technique is needed to estimate the AoA. In other words, the hardware and computational complexities of SBSs are low. However, if the power of the received signal is lower than the receiver sensitivity; i.e., at low signal to noise ratio (SNR), SBS will fail to estimate the AoA.
AoA estimation techniques that use AAS can be divided into two main groups: so-called “classical” techniques and subspace techniques. The classical AoA techniques are Delay and Sum, also known as the Bartlett technique, and Minimum Variance Distortionless (MVDR), also known as the Capon technique. By steering the beams electronically and estimating the power spectrum of the received signal, the AoAs are estimated as being the peaks in the spatial power spectrum. The main drawback of the Bartlett technique is that signal impinging with an angular separation less than
      2    ⁢                  ⁢    π    Mcannot be resolved. The Capon technique relatively solves the angular resolution drawback of the Bartlett method at the cost of more baseband processing needed for matrix inversion.
The subspace techniques are based on the concept that the signal subspace is orthogonal to the noise subspace. The most widely used technique in this group is the MUltiple SIgnal Classification (MUSIC) technique. The MUSIC technique provides the highest angular resolution and can operate at low SNR levels. This comes at the cost that it requires a full a priori knowledge of the number of sources and the array response, whether it is measured and stored or computed analytically. The signal and noise subspaces are distinguished through an eigen-decomposition operation applied at the covariance matrix of the received signal. This operation requires a substantial computational complexity.
Thus, a method and apparatus for angle of arrival estimation addressing the aforementioned problems is desired.